SAP wants to speed up how analytics adapt to change. It’s doing that by embedding SAP Predictive Analytics’ machine learning capabilities in S/4Hana.

“When you take something rules-based, you are not able to adapt predictions to new data,” said Mike Flannagan, SAP’s senior vice president for analytics, ahead of the company’s Sapphire Now customer conference in Orlando.

“The power of machine learning is you are able to continually update the model. Your model is running against all the data it has seen so far.”

But there’s another stumbling block to that: the computing power required for machine learning systems. “Most business apps aren’t robust enough to handle the machine learning computation,” said Flannagan. S4/Hana, on the other hand, is fast enough to embed machine-learning prediction in a core ERP system, something that was previously only possible with rules-based prediction, he said.

SAP wants to speed up how analytics adapt to change. It’s doing that by embedding SAP Predictive Analytics’ machine learning capabilities in S/4Hana.

“When you take something rules-based, you are not able to adapt predictions to new data,” said Mike Flannagan, SAP’s senior vice president for analytics, ahead of the company’s Sapphire Now customer conference in Orlando.

“The power of machine learning is you are able to continually update the model. Your model is running against all the data it has seen so far.”

But there’s another stumbling block to that: the computing power required for machine learning systems. “Most business apps aren’t robust enough to handle the machine learning computation,” said Flannagan. S4/Hana, on the other hand, is fast enough to embed machine-learning prediction in a core ERP system, something that was previously only possible with rules-based prediction, he said.

IBM’s revenue continued to decline in the second quarter but growth in some of its strategic initiatives like cloud computing and data analytics suggest that the company may be on track in its transition plans.

The Armonk, New York, company said Monday that revenue from its new “strategic imperatives” like cloud, analytics and security increased by 12 percent year-on-year to $ 8.3 billion. That increase was, however, lower than the growth the company had reported in these businesses in the first quarter.

When business people talk Big Data, they often focus on the complexity of dealing with enormous data volume, but that’s changing. Volume alone does not pose the challenge it once did. For example, the Panama Papers leaked data was about 2.6 Terabytes. You could buy a hard drive sufficient to store all of it at an ordinary electronics shop for less than $ 100.

Sidewalks Labs, a unit of Google parent-company Alphabet, is teaming up with the U.S. Department of Transportation to build a data and analytics platform that promises to help cities understand where people go and how they get there.

The goal is to help better design transportation infrastructure to suit a city’s needs.

The platform, called Flow, will rely on one of Alphabet’s core strengths: collecting, analyzing and visualizing vast amounts of data.

The system will help cities identify congestion and areas that are underserved by public transportation, enabling planners to come up with a better citywide plan that uses current and new forms of transportation, such as ride-sharing, Sidewalk says. That’s getting more important as commute times and distances grow longer.

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Announced on Tuesday, SAP Hana Vora is an in-memory query engine that taps the Apache Spark execution framework to deliver interactive analytics on Hadoop.

By extending Hana’s reach to include distributed data in the Hadoop ecosystem, the tool is designed to help data scientists and developers combine corporate and external data in their analyses. That, in turn, means that incoming data from customers, partners and smart devices can be integrated with that from internal enterprise processes, giving companies better context with which to make decisions, SAP said.

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